[ccp4bb] Staff Scientist position in Protein Technologies Center at St. Jude

[Miller, Darcie]

Staff Scientist

Job ID: 39237, Department Structural Biology, Job Location: US-TN-Memphis

https://careers-stjude.icims.com/jobs/4190/staff-scientist/job

Overview

We are seeking outstanding biochemists, with expertise in protein purification 
and/or protein engineering to join our new Protein Technologies Center (PTC) 
within the Structural Biology Department at St. Jude Children’s Research 
Hospital. The PTC is a multidisciplinary team with capabilities in protein 
engineering, cloning, expression, purification, and analysis of proteins. The 
PTC is responsible for the optimization, production and assessment of difficult 
protein targets for structural studies, thereby supporting structural 
biologists and other researchers at St. Jude to focus on making big 
discoveries. This is a bench-based scientist role where you will be providing 
pivotal support to several projects both strategically and tactically.

Responsibilities

1.  Design, develop and optimize protein expression, purification 
and characterization methods like stability, size distribution and conformation

2.  Engineer the proteins, including membrane proteins, immune 
molecules, complex multi-domain proteins and fusion partners (Chimeras) which 
would aid in the stabilization and/or increase the chance of success in protein 
production, purification and structure-function studies.

3.  Purification and analysis of the recombinant proteins, 
preferably membrane proteins, using FPLC and U/HPLC and also maintenance of the 
chromatography systems

4.  Contribution to the entire structural biology workflow: - 
cloning and expression in bacteria, insect or mammalian expression systems

5.  Generate antibodies (or Synthetic Antigen Binders) through 
hybridoma, phage, yeast, or other panning technology

6.  Work independently on the design, execution, and interpretation 
of experimental results

7.  Train and mentor research associates, students and/or 
postdoctoral associates who seek to leverage the Protein Technologies Center’s 
capabilities at St. Jude

Minimum Education

PhD in the area of molecular biology, biochemistry, protein engineering, or any 
related discipline.



Minimum Experience

A minimum of five (5) years of relevant and productive (combined) years 
postdoctoral research associate or five (5) years of combined academic 
experience at the postdoctoral level or above.



Please send your CV and enquiries to 
ravi.kalat...@stjude.org







Email Disclaimer: www.stjude.org/emaildisclaimer
Consultation Disclaimer: www.stjude.org/consultationdisclaimer



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Re: [ccp4bb] Off topic: 'Difficult' Datasets for Processing Practice

[James Holton]

It was brought to my attention that the link to the preprint I provided 
below doesn't work, but this one does:


https://www.biorxiv.org/content/early/2018/08/18/394965

Thanks to Folmer Fredslund for pointing this out to me!

-James Holton
MAD Scientist

On 9/21/2018 3:50 PM, James Holton wrote:
For teaching purposes I have found that controlled pairs of data sets 
are most instructive.  You are right that an easy one-button-push 
processing run tells you nothing, but so does a 
bang-it-crashed-now-what data set.  Most useful are two data sets that 
are identical in every respect but one, and that one thing is the 
point you are trying to get across.  It's hard to collect such 
perfectly paired data sets, so I ended up just simulating them. I 
deliberately chose a high-symmetry space group to keep the download 
size small. You can download them from here:


http://bl831.als.lbl.gov/~jamesh/workshop/

These five datasets represent the four biggest problems I see users 
have when trying to solve structures: 1) poor anomalous signal, 2) 
overlaps from a bad crystal orientation, 3) hidden radiation damage to 
sites, and 4) ice rings.  The 5th "goodsignal" dataset is the positive 
control.


The web page contains everything from images to processed MTZ files, 
maps and the "right answer" in pdb and mtz format.  A slightly more 
"realistic" version with a bigger download size is here:


http://bl831.als.lbl.gov/~jamesh/workshop2/

This is the one I used for my "weak anomalous challenge" a few years 
back. The teaching advantage is that you can use the image-mixer 
script to modulate the severity of problems like ice rings and 
anomalous signal.  If you make a competition of it, people tend to get 
more interested.


When it comes to beam centers, it is not all that hard to take a data 
set with a "correct" beam center and just edit the headers. How you do 
this depends on the file format, but I have some instructions for 
editing images in general here:


http://bl831.als.lbl.gov/~jamesh/bin_stuff/

In general, you can usually separate the header from the data with the 
unix command "head" or "dd", edit the header with your favorite text 
editor, and then put the two parts back together with "cat". As for 
which beam center is "correct", it is important to tell your students 
that that depends on which software you are using.  I wrote all this 
down in the last paragraph on page 7 of this doc:


https://submit.biorxiv.org/submission/pdf?msid=BIORXIV/2018/394965

This doc also describes another simulated data set that demonstrates 
the challenges of combining lots of short wedges together.  May or may 
not be too advanced a topic for your students?  Or maybe not. As you 
can guess I'm experimenting with biorxiv.  So far, no comments.


Good luck with your class!

-James Holton
MAD Scientist


On 9/19/2018 5:15 PM, Whitley, Matthew J wrote:

Dear colleagues,

For teaching purposes, I am looking for a small number (< 5) of
macromolecular diffraction datasets (raw images) that might be
considered 'difficult' for a beginning crystallography student to
process.  By 'difficult' I generally mean not able to be processed
automatically by a common processing package (XDS, Mosflm, DIALS, etc)
using default settings, i.e., no black box "click and done" processing.
The datasets I am looking for would have some stumbling block such as
incorrect experimental parameters recorded in the image headers,
multiple lattices that cause indexing to fail, datasets for which
determining the correct space group is tricky, datasets for experiments
in which the crystal slipped or moved in the beam, or anything else you
can think of.  The idea is for these beginning students to examine
several datasets that highlight various phenomena that can lead one
astray during processing.

A good candidate dataset would also ideally comprise a modest number of
images so as to keep integration time to a minimum.  Factors that are
mostly irrelevant for my purpose: resolution (as long as better than
~3.5 Å), source (home vs synchrotron), presence/absence of anomalous
scattering,  presence/absence of ligands, monomeric vs oligomeric
structures, etc.  Also, to be clear, I am not looking for datasets that
have so many pathologies that they would require many long hours of work
for an expert to process correctly.

I have checked public repositories such as proteindiffraction.org and
SBGrid databank, but all of the datasets I acquired from these sources
process satisfactorily with little effort, and in any event I know of no
way to search for 'challenging' datasets.  (I also wonder whether
anybody is in the habit of depositing, shall we say, less-than-pristine
images to public repositories?)

If you know of such a dataset that is already publicly available, or if
you have such a dataset that you are willing to share for solely
educational purposes, I would appreciate hearing from you, either on- or
off-list.

Thank you in advance for your suggestions.

Re: [ccp4bb] Off topic: 'Difficult' Datasets for Processing Practice

[Andreas Förster]

Hi James,

you’re probably aware of this but you can edit CBF headers in place with
sed. That’s what I do when I make the detector on my diffractometer go
closer than the hardware limit.

All best - Andreas
On Sat, 22 Sep 2018 at 00:51, James Holton 
wrote:

> For teaching purposes I have found that controlled pairs of data sets
> are most instructive.  You are right that an easy one-button-push
> processing run tells you nothing, but so does a bang-it-crashed-now-what
> data set.  Most useful are two data sets that are identical in every
> respect but one, and that one thing is the point you are trying to get
> across.  It's hard to collect such perfectly paired data sets, so I
> ended up just simulating them. I deliberately chose a high-symmetry
> space group to keep the download size small. You can download them from
> here:
>
> http://bl831.als.lbl.gov/~jamesh/workshop/
>
> These five datasets represent the four biggest problems I see users have
> when trying to solve structures: 1) poor anomalous signal, 2) overlaps
> from a bad crystal orientation, 3) hidden radiation damage to sites, and
> 4) ice rings.  The 5th "goodsignal" dataset is the positive control.
>
> The web page contains everything from images to processed MTZ files,
> maps and the "right answer" in pdb and mtz format.  A slightly more
> "realistic" version with a bigger download size is here:
>
> http://bl831.als.lbl.gov/~jamesh/workshop2/
>
> This is the one I used for my "weak anomalous challenge" a few years
> back. The teaching advantage is that you can use the image-mixer script
> to modulate the severity of problems like ice rings and anomalous
> signal.  If you make a competition of it, people tend to get more
> interested.
>
> When it comes to beam centers, it is not all that hard to take a data
> set with a "correct" beam center and just edit the headers. How you do
> this depends on the file format, but I have some instructions for
> editing images in general here:
>
> http://bl831.als.lbl.gov/~jamesh/bin_stuff/
>
> In general, you can usually separate the header from the data with the
> unix command "head" or "dd", edit the header with your favorite text
> editor, and then put the two parts back together with "cat". As for
> which beam center is "correct", it is important to tell your students
> that that depends on which software you are using.  I wrote all this
> down in the last paragraph on page 7 of this doc:
>
> https://submit.biorxiv.org/submission/pdf?msid=BIORXIV/2018/394965
>
> This doc also describes another simulated data set that demonstrates the
> challenges of combining lots of short wedges together.  May or may not
> be too advanced a topic for your students?  Or maybe not. As you can
> guess I'm experimenting with biorxiv.  So far, no comments.
>
> Good luck with your class!
>
> -James Holton
> MAD Scientist
>
>
> On 9/19/2018 5:15 PM, Whitley, Matthew J wrote:
> > Dear colleagues,
> >
> > For teaching purposes, I am looking for a small number (< 5) of
> > macromolecular diffraction datasets (raw images) that might be
> > considered 'difficult' for a beginning crystallography student to
> > process.  By 'difficult' I generally mean not able to be processed
> > automatically by a common processing package (XDS, Mosflm, DIALS, etc)
> > using default settings, i.e., no black box "click and done" processing.
> > The datasets I am looking for would have some stumbling block such as
> > incorrect experimental parameters recorded in the image headers,
> > multiple lattices that cause indexing to fail, datasets for which
> > determining the correct space group is tricky, datasets for experiments
> > in which the crystal slipped or moved in the beam, or anything else you
> > can think of.  The idea is for these beginning students to examine
> > several datasets that highlight various phenomena that can lead one
> > astray during processing.
> >
> > A good candidate dataset would also ideally comprise a modest number of
> > images so as to keep integration time to a minimum.  Factors that are
> > mostly irrelevant for my purpose: resolution (as long as better than
> > ~3.5 Å), source (home vs synchrotron), presence/absence of anomalous
> > scattering,  presence/absence of ligands, monomeric vs oligomeric
> > structures, etc.  Also, to be clear, I am not looking for datasets that
> > have so many pathologies that they would require many long hours of work
> > for an expert to process correctly.
> >
> > I have checked public repositories such as proteindiffraction.org and
> > SBGrid databank, but all of the datasets I acquired from these sources
> > process satisfactorily with little effort, and in any event I know of no
> > way to search for 'challenging' datasets.  (I also wonder whether
> > anybody is in the habit of depositing, shall we say, less-than-pristine
> > images to public repositories?)
> >
> > If you know of such a dataset that is already publicly available, or if
> > you have such a dataset that you are 

[ccp4bb] Recruiting fragment/XChem crystallographers

[Frank von Delft]

Hi all -

We have vacancies at SGC (in my and Prof. Paul Brennan's groups) for 
crystallographers interested in driving a series of new genetically 
validated targets (inflammation and Alzheimers) from gene to XChem 
fragment screening and beyond to potency, and helping figure out how to 
do all of this a lot better than we currently can.


Link is here 
, 
and deadline is in two weeks (October 5th).


Frank

--
Prof Frank von Delft
Associate Professor
Principal Investigator: Protein Crystallography
Structural Genomics Consortium
Oxford University
+44 1865 617583 (office: W,F)

Principal Beamline Scientist: I04-1
Diamond Light Source
+44 1235 778997 (office: M,T,T)
+44 7471 026103 (mobile)





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